scholarly journals Characteristics of Battery SOC According to Drive Output and Battery Capacity of Parallel Hybrid Electric Vehicle

2020 ◽  
Vol 10 (8) ◽  
pp. 2833 ◽  
Author(s):  
Insu Cho ◽  
Jinwook Lee
Keyword(s):  
Numerical Analysis ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Fuel Efficiency ◽  
Lithium Ion ◽  
Electrical Energy ◽  
Simulation Code ◽  
Vehicle Simulation ◽  
Battery Capacity ◽  
Hybrid Electric

To mitigate global warming caused by vehicles, emission regulations have been implemented for all automobiles. Hybrid electric vehicles (HEVs) are being designed to meet consumer demand for eco-friendly vehicles that offer increased power and improved fuel efficiency. HEVs are powered by an internal combustion engine (ICE) in combination with one or more electric motors that use electrical energy stored in a secondary battery, which is typically a lithium-based battery. With the use of such a hybrid drivetrain system, the fuel efficiency can be improved over that of conventional ICE vehicles. In this study, we conducted a vehicle-driving experiment to evaluate a transmission-mounted electric device (TMED) type parallel HEV using a chassis dynamometer and on-board diagnostics (OBD) signal-measuring equipment. In addition, we performed a numerical analysis using the CRUISE vehicle simulation code with experimental data. In our analysis, the engine output, which affects the torque of the drive motor, and the capacity (energy density) of the lithium-ion polymer battery were set as variables that affect the fuel-economy performance. As a result of this numerical analysis, a hybrid power-drivetrain model based on CRUISE was developed, and the current balance was evaluated according to the change in the battery capacity. We found that the battery state of charge (SOC) dropped because of a decrease in battery capacity. Thus, we predicted that the lithium-ion battery capacity would be reduced.

Configuration Study of Hybrid Electric Power Pack for Tracked Combat Vehicles

2017 ◽  
Vol 67 (4) ◽  
pp. 354 ◽  
Author(s):  
P. Sivakumar ◽  
Rajaseeli Reginald ◽  
G. Venkatesan ◽  
Hari Viswanath ◽  
T. Selvathai
Keyword(s):  
Electric Power ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Fuel Efficiency ◽  
Optimal Operation ◽  
Regenerative Braking ◽  
Electric Motors ◽  
Power Train ◽  
Military Vehicles ◽  
Hybrid Electric

<p>In recent years, there is growing interest in hybridisation of military vehicles due to the features and advantages offered by the technology. Generally, the hybrid electric vehicle (HEV) is propelled by a combination of electric motors and internal combustion engine (ICE). Hybrid electric combat vehicles, when compared with conventional vehicles, have the advantages of improved fuel efficiency and drivability due to optimal operation of ICE, regenerative braking and silent operation capability. Limitations related to key technologies such as compact electric motors/generators, power electronics and energy storage systems that are required to operate under extreme environmental conditions pose challenges to the development of hybrid electric power pack. Technical challenges of HEV technologies considering futuristic applications of combat vehicles is described. The configuration specification of hybrid electric power train architecture suited to deliver high automotive performance and power demands for infantry combat vehicles (ICV) is also discussed.</p>

Simulation and Analysis of Hybrid Electric Vehicle Powertrain

2011 ◽  
Vol 230-232 ◽  
pp. 964-967 ◽  
Author(s):  
Fa Chao Jiang ◽  
Lin Li ◽  
Mo Lin Wang
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
High Efficiency ◽  
Combustion Engine ◽  
Fuel Efficiency ◽  
Flow Simulation ◽  
Simulation Method ◽  
Simulation Software ◽  
Optimizing Design ◽  
Hybrid Electric

By optimizing design and reasonable matching, internal combustion engine can operate under the condition of high efficiency to improve fuel efficiency and reduce exhaust emissions. This paper use reverse energy flow simulation method, transmission of speed and torque as the main line, based on the establishing of engine, motor, battery and other models, analyzing HEV parameter and the request of driving force, motor and battery. Regarding one kind of Hybrid Electric Vehicle as the research object, the mathematics model of power and economic performance was established. A PHEV performance simulation software was developed by using MATLAB/ SIMULINK. The demand of Hybrid Electric Vehicle to the power of motor and battery were analyzed on the given Driving Cycle.

A Fuzzy Based Propulsion Selection for Fuel Efficiency in Hybrid Electric Vehicle

2018 ◽  
Author(s):  
Debraj Bhattacharjee ◽  
Prabha Bhola ◽  
Pranab K. Dan
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Fossil Fuel ◽  
Combustion Engine ◽  
Electronic Control Unit ◽  
Fuel Efficiency ◽  
Control Unit ◽  
Control Logic ◽  
Hybrid Electric ◽  
On The Road

This article proposes a fuzzy based fuel-efficient propulsion selection logic for a hybrid electric vehicle (HEV) in ‘Highway Fuel Economy Test (HWFET)’ driving cycle. Optimal utilisation of combustion engine, in HEV, reduces the fossil fuel consumption. This can be realized through an electronic control unit, embedded with effective propulsion selection logic that governs the power split device in series-parallel HEV. A propulsion control logic, based on the road gradeability, velocity, torque demand and vehicle battery state of charge (SOC) is presented in this article. A comparison with conventional propulsion selection logic based system shows that the HEV modelled with proposed fuzzy based one, results in better speed tracking with steep road grades, as it provides better torque supply at desired speed points. The analysis indicates a reduction in consumption of both the fossil fuel as well as the electrical fuel (SOC).

Emission Implications of Plug-in Hybrid Electric Vehicles Through an Empirical Exploration of Engine Starts

2021 ◽  
pp. 036119812110038
Author(s):  
Vaishnavi Chaitanya Karanam ◽  
Gil Tal
Keyword(s):  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Inverse Correlation ◽  
Power Requirement ◽  
Vehicle Data ◽  
Battery Capacity ◽  
Hybrid Electric ◽  
Cold Starts ◽  
Engine Start ◽  
Toyota Prius

This paper aims to characterize the engine start activity profiles and emission potential of various plug-in hybrid electric vehicle (PHEV) models by examining the characteristics associated with engine starts, identifying the travel conditions that trigger engine starts, and determining the frequency of different types of engine starts. The study analyzed on-road vehicle data from six PHEV models: Toyota Prius Plug-in, Ford C-Max Energi, Ford C-Max Fusion, Toyota Prius Prime, Chrysler Pacifica, and Chevrolet Volt. An analysis on travel conditions before engine starts revealed that low state-of-charge is the dominant engine start trigger for PHEVs with high all-electric range whereas high vehicle power requirement is the most critical trigger for PHEVs with low all-electric range. For PHEVs with mid-range capabilities, several vehicle specifications, ranging from peak electric motor power to curb weight, could be engine start determinants. A strong inverse correlation exists between battery capacity and the annual frequency of engine starts but this relationship does not hold for cold and high-power cold starts. Both the low and the high battery capacity PHEVs logged fewer cold starts than the mid-sized battery vehicles, indicating that there could be a fundamental tradeoff between engine start emissions and fuel displacement for PHEVs to a certain degree. Despite this tradeoff, all PHEV models in the study logged fewer cold starts than comparable conventional internal combustion engine vehicles, performing the same trips. Ultimately, long-range PHEVs with high battery capacity are found to be ideal for both curbing start emissions and reducing fuel use.

Stirling system optimization for series hybrid electric vehicles

2021 ◽  
pp. 095440702110180
Author(s):  
Charbel R Ghanem ◽  
Elio N Gereige ◽  
Wissam S Bou Nader ◽  
Charbel J Mansour
Keyword(s):  
Fuel Consumption ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Optimization Technique ◽  
System Optimization ◽  
Energy Management Strategy ◽  
Fuel Savings ◽  
Auxiliary Power ◽  
Hybrid Electric ◽  
External Combustion

There have been many studies conducted to replace the conventional internal combustion engine (ICE) with a more efficient engine, due to increasing regulations over vehicles’ emissions. Throughout the years, several external combustion engines were considered as alternatives to these traditional ICEs for their intrinsic benefits, among which are Stirling machines. These were formerly utilized in conventional powertrains; however, they were not implemented in hybrid vehicles. The purpose of this study is to investigate the possibility of implementing a Stirling engine in a series hybrid electric vehicle (SHEV) to substitute the ICE. Exergy analysis was conducted on a mathematical model, which was developed based on a real simple Stirling, to pinpoint the room for improvements. Then, based on this analysis, other configurations were retrieved to reduce exergy losses. Consequently, a Stirling-SHEV was modeled, to be integrated as auxiliary power unit (APU). Hereafter, through an exergo-technological detailed selection, the best configuration was found to be the Regenerative Reheat two stages serial Stirling (RRe-n2-S), offering the best efficiency and power combination. Then, this configuration was compared with the Regenerative Stirling (R-S) and the ICE in terms of fuel consumption, in the developed SHEV on the WLTC. This was performed using an Energy Management Strategy (EMS) consisting of a bi-level optimization technique, combining the Non-dominated Sorting Genetic Algorithm (NSGA) with the Dynamic Programming (DP). This arrangement is used to diminish the fuel consumption, while considering the reduction of the APU’s ON/OFF switching times, avoiding technical issues. Results prioritized the RRe-n2-S presenting 12.1% fuel savings compared to the ICE and 14.1% savings compared to the R-S.

Powertrain Matching Based on Driving Cycle for Fuel Cell Hybrid Electric Vehicle

2013 ◽  
Vol 288 ◽  
pp. 142-147 ◽  
Author(s):  
Shang An Gao ◽  
Xi Ming Wang ◽  
Hong Wen He ◽  
Hong Qiang Guo ◽  
Heng Lu Tang
Keyword(s):  
Fuel Cell ◽  
Electric Vehicle ◽  
Cell Hybrid ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Driving Cycle ◽  
Power Performance ◽  
Matching Method ◽  
Hybrid Electric ◽  
Fuel Cell Hybrid

Fuel cell hybrid electric vehicle (FCHEV) is one of the most efficient technologies to solve the problems of the energy shortage and the air pollution caused by the internal-combustion engine vehicles, and its performance strongly depends on the powertrains’ matching and its energy control strategy. The theoretic matching method only based on the theoretical equation of kinetic equilibrium, which is a traditional method, could not take fully use of the advantages of FCHEV under a certain driving cycle because it doesn’t consider the target driving cycle. In order to match the powertrain that operates more efficiently under the target driving cycle, the matching method based on driving cycle is studied. The powertrain of a fuel cell hybrid electric bus (FCHEB) is matched, modeled and simulated on the AVL CRUISE. The simulation results show that the FCHEB has remarkable power performance and fuel economy.

Optimal Dual-Mode Hybrid Electric Vehicle Powertrain Architecture Design for a Variety of Loading Scenarios

2014 ◽  
Author(s):  
Alparslan Emrah Bayrak ◽  
Yi Ren ◽  
Panos Y. Papalambros
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Fuel Efficiency ◽  
Architecture Design ◽  
Optimization Strategy ◽  
Passenger Cars ◽  
Hybrid Electric ◽  
Distribution Of Power ◽  
Architecture Development ◽  
Vehicle Powertrain

A hybrid-electric vehicle powertrain architecture consists of single or multiple driving modes, i.e., connection arrangements among engine, motors and vehicle output shaft that determine distribution of power. While most architecture development work to date has focused primarily on passenger cars, interest has been growing in exploring architectures for special-purpose vehicles such as vans or trucks for civilian and military applications, whose weights or payloads can vary significantly during operations. Previous findings show that the optimal architecture can be sensitive to vehicle weight. In this paper we investigate architecture design under a distribution of vehicle weights, using a simulation-based design optimization strategy with nested supervisory optimal control and accounting for powertrain complexity. Results show that an architecture under a single load has significant differences and lower fuel efficiency than an architecture designed to work under a variety of loading scenarios.

SIMULATION OF HYBRID ELECTRIC VEHICLE BASED ON A SERIES DRIVE TRAIN LAYOUT

2016 ◽  
Vol 78 (6) ◽  
Author(s):  
Mohd Sabirin Rahmat ◽  
Fauzi Ahmad ◽  
Ahmad Kamal Mat Yamin ◽  
Noreffendy Tamaldin ◽  
Vimal Rau Aparow ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Automatic Transmission ◽  
Permanent Magnet Synchronous Motor ◽  
Drive Train ◽  
Maximum Speed ◽  
Power Train ◽  
Human In The Loop ◽  
Hybrid Electric

This paper provided a validated modeling and a simulation of a 6 degree freedom vehicle longitudinal model and drive-train component in a series hybrid electric vehicle. The 6-DOF vehicle dynamics model consisted of tire subsystems, permanent magnet synchronous motor which acted as the prime mover coupled with an automatic transmission, hydraulic brake subsystem, battery subsystem, alternator subsystem and internal combustion engine to supply the rotational input to the alternator. A speed and torque tracking control systems of the electric power train were developed to make sure that the power train was able to produce the desired throttle torque in accelerating the vehicle. A human-in-the-loop-simulation was utilized as a mechanism to evaluate the effectiveness of the proposed hybrid electric vehicle. The proposed simulation was used as the preliminary result in identifying the capability of the vehicle in terms of the maximum speed produced by the vehicle and the capability of the alternator to recharge the battery. Several tests had been done during the simulation, namely sudden acceleration, acceleration and braking test and unbounded motion. The results of the simulation showed that the proposed hybrid electric vehicle can produce a speed of up to 70 km/h with a reasonable charging rate to the battery. The findings from this study can be considered in terms of design, optimization and implementation in a real vehicle.

scholarly journals Development of a Hybrid Electric Vehicle Simulation Tool with a Rule-Based Topology

2021 ◽  
Vol 11 (23) ◽  
pp. 11319
Author(s):  
Hyun Woo Won
Keyword(s):  
Hybrid Electric Vehicle ◽  
Hybrid Simulation ◽  
Rule Base ◽  
Simulation Tool ◽  
Control Logic ◽  
Rule Based ◽  
Vehicle Simulation ◽  
Wide Range ◽  
Hybrid Electric ◽  
And Control

The performance of hybrid electric vehicles (HEVs) greatly depends on the various sub-system components and their architecture, and designers need comprehensive reviews of HEVs before vehicle investigation and manufacturing. Simulations facilitate development of virtual prototypes that make it possible to rapidly see the effects of design modifications, avoiding the need to manufacture multiple expensive physical prototypes. To achieve the required levels of emissions and hardware costs, designers must use control strategies and tools such as computational modeling and optimization. However, most hybrid simulation tools do not share their principles and control logic algorithms in the open literature. With this motivation, the author developed a hybrid simulation tool with a rule-based topology. The major advantage of this tool is enhanced flexibility to choose different control and energy management strategies, enabling the user to explore a wide range of hybrid topologies. The tool provides the user with the ability to modify any sub-system according to one’s own requirements. In addition, the author introduces a simple logic control for a rule-base strategy as an example to show the flexibility of the tool in allowing the adaptation of any logic algorithm by the user. The results match the experimental data quite well. Details regarding modeling principle and control logic are provided for the user’s benefit.

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